This week on No Priors, Sarah and Elad do another hangout to answer listener questions. Topics include debunking common misconceptions about AI and its implications on the world, the analogy to nuclear power and nuclear safety, the impact of larger context windows, developer productivity, incumbent announcements of AI products, and some requests for (fat) startups.No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode.Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @SchimpfBrianShow Notes:[00:21] - What Are People Getting Wrong About AI Right Now? / New Capabilities of NLP[04:35] - Nuclear Power and Safety Concerns[11:12] - Emerging AI Companies and Research[15:54] - China's Hardware Sanctions and Funding Ramp[20:34] - Innovation in Heterogeneous Compute Infrastructure[28:08] - Enterprise Stack and Decision Making[33:44] - Data's Impact on the World

Today on No Priors, we discuss defense technology, AI, drones, and autonomous vehicles (think giant submarine drones!) with Brian Schimpf, the co-founder and CEO of Anduril, a next-generation defense technology company. From his early days of coding at age 12 to working on self-driving cars, and finally founding Anduril, Brian's incredible journey led him to create innovative solutions for pressing defense problems.This episode covers the impact of AI, intelligent software, and other technologies to defense. We discuss the challenges of deploying and selling technology in the government spaceBrian shared his perspective on building general-purpose defense technology, the importance of a software-first approach, and how Anduril is working to solve urgent defense problems with speed and efficiency.As we wrapped up our conversation, we touched on the recent shift in the low cost of space launch, which has changed the way the US thinks about defense. We examined the proliferation of satellites, drones, and hypersonic missiles, and how these technologies can be applied, scaled, and built in a way that can fundamentally shift America's approach to defense. Don't miss this fascinating episode with Brian Schimpf as we uncover the cutting edge of defense technology and its implications for the future.No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode.Show Links: May 16, 2023: AI in Military Operations and How We Can Prevent It From Outsized Effects May 9, 2023: CNBC Disruptor 50 - Anduril Industries Anduril Website Anduril Newsroom Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @SchimpfBrianShow Notes:[0:00:01] - Exploring AI in Defense Tech[0:05:15] - Lower Cost Defense With Intelligent Software[0:15:10] - Building General Purpose Defense Technology[0:20:41] - Autonomy in Defense Challenges[0:25:05] - Machine Learning in Defense & Intelligence[0:29:06] - Scaling a Defense Tech Company[0:37:08] - The Future of Defense Technology[0:46:53] - Allied Forces and Washington Engagement[0:51:47] - Discussion on Leadership Popularity

In this episode, Sarah and Elad speak with Microsoft CTO Kevin Scott about his unlikely journey from rural Virginia to becoming the driving force behind Microsoft's AI strategy. Sarah and Elad discuss the partnership that Kevin helped forge between Microsoft and OpenAI and explore the vision both companies have for the future of AI. They also discuss yesterday’s announcement of “copilots” across the Microsoft product suite, Microsoft’s GPU computing budget, the potential impact of open source AI models in the tech industry, the future of AI in relation to jobs, why Kevin is bullish on creative and physical work, and predictions for progress in AI this year.No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode.Show Links: May 23, 2023: The Verge - Microsoft CTO Kevin Scott Thinks Sydney Might Make a Comeback May 23, 2023: Microsoft Outlines Framework For Building AI Apps and Copilots January 10, 2023: A Conversation with Kevin Scott: What’s Next In AI Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @kevin_scottShow Notes:[00:00] - Kevin Scott's Journey to Microsoft CTO[12:44] - Microsoft and Open AI Partnership[21:18] - The Future of Open Source AI[32:12] - AI for Everyone[45:29] - AI and the Future of Jobs[51:44] - The Future of AI and Regulation[58:10] - Taking a Global Perspective

What if AI could revolutionize healthcare with advanced language learning models? Sarah and Elad welcome Karan Singhal, Staff Software Engineer at Google Research, who specializes in medical AI and the development of MedPaLM2. On this episode, Karan emphasizes the importance of safety in medical AI applications and how language models like MedPaLM2 have the potential to augment scientific workflows and transform the standard of care.Other topics include the best workflows for AI integration, the potential impact of AI on drug discoveries, how AI can serve as a physician's assistant, and how privacy-preserving machine learning and federated learning can protect patient data, while pushing the boundaries of medical innovation.No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode.Show Links: May 10, 2023: PaLM 2 Announcement April 13, 2023: A Responsible Path to Generative AI in Healthcare March 31, 2023: Scientific American article on Med-PaLM February 28, 2023: The Economist article on Med-PaLM KaranSinghal.com Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @thekaransinghalShow Notes:[00:22] - Google's Medical AI Development[08:57] - Medical Language Model and MedPaLM 2 Improvements[18:18] - Safety, cost/benefit decisions, drug discovery, health information, AI applications, and AI as a physician's assistant.[24:51] - Privacy Concerns - HIPAA's implications, privacy-preserving machine learning, and advances in GPT-4 and MedPOM2.[37:43] - Large Language Models in Healthcare and short/long term use.

Mustafa Suleyman, co-founder of DeepMind and now co-founder and CEO of Inflection AI, joins Sarah and Elad to discuss how his interests in counseling, conflict resolution, and intelligence led him to start an AI lab that pioneered deep reinforcement learning, lead applied AI and policy efforts at Google, and more recently found Inflection and launch Pi.Mustafa offers insights on the changing structure of the web, the pressure Google faces in the age of AI personalization, predictions for model architectures, how to measure emotional intelligence in AIs, and the thinking behind Pi: the AI companion that knows you, is aligned to your interests, and provides companionship.Sarah and Elad also discuss Mustafa’s upcoming book, The Coming Wave (release September 12, 2023), which examines the political ramifications of AI and digital biology revolutions.No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode.Show Links: Forbes - Startup From Reid Hoffman and Mustafa Suleyman Debuts ChatBot Inflection.ai Mustafa-Suleyman.ai Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @mustafasuleymnShow Notes:[00:06] - From Conflict Resolution to AI Pioneering[10:36] - Defining Intelligence[15:32] - DeepMind's Journey and Breakthroughs[24:45] - The Future of Personal AI Companionship[33:22] - AI and the Future of Personalized Content[41:49] - The Launch of Pi[51:12] - Mustafa’s New Book The Coming Wave

How do you personalize AI models? A popular school of thought in AI is to just dump all the data you need into pre-training or fine tuning. But that may be less efficient and less controllable than alternatives — using AI models as a reasoning engine against external data sources.Kelvin Guu, Senior Staff Research Scientist at Google, joins Sarah and Elad this week to talk about retrieval, memory, training data attribution and model orchestration. At Google, he led some of the first efforts to leverage pre-trained LMs and neural retrievers, with >30 launches across multiple products. He has done some of the earliest work on retrieval-augmented language models (REALM) and training LLMs to follow instructions (FLAN).No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode.Show Links: Kelvin Guu Website Google Scholar FLAN: Finetuned Language Models Are Zero-Shot Learners Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs ROME: Locating and Editing Factual Associations in GPT Branch-Train-Merge: Scaling Expert Language Models with Unsupervised Domain Discovery Large Language Models Struggle to Learn Long-Tail Knowledge  Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Kelvin_GuuShow Notes:[1:44] - Kelvin’s background in math, statistics and natural language processing at Stanford[3:24] - The questions driving the REALM Paper[7:08] - Frameworks around retrieval augmentation & expert models[10:16] - Why is modularity important[11:36] - FLAN Paper and instruction following[13:28] - Updating model weights in real time and other continuous learning methods[15:08] - Simfluence Paper & explainability with large language models[18:11] - ROME paper, “Model Surgery” exciting research areas[19:51] - Personal opinions and thoughts on AI agents & research[24:59] - How the human brain compares to AGI regarding memory and emotions[28:08] - How models become more contextually available[30:45] - Accessibility of models[33:47] - Advice to future researchers

This week on No Priors, Sarah and Elad answer listener questions about tech and AI. Topics covered include the evolution of open-source models, Elon AI, regulating AI, areas of opportunity, and AI hype in the investing environment. Sarah and Elad also delve into the impact of AI on drug development and healthcare, and the balance between regulation and innovation.Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGilShow Notes: [0:00:06] - The March of Progress for Open Source Foundation Models [0:06:00] - Should AI Be Regulated?[0:13:49] - Investing in AI and Exploring the AI Opportunity Landscape[0:23:28] - The Impact of Regulation on Innovation[0:31:55] - AI in Healthcare and Biotech

So much of the AI conversation today revolves around models and new applications. But this AI revolution would not be possible without one thing – GPUs, Nvidia GPUs.The Nvidia A100 is the workhorse of today’s AI ecosystem. This week on No Priors, Sarah Guo and Elad Gil sit down with Jensen Huang, the founder and CEO of NVIDIA, at their Santa Clara headquarters. Jensen co-founded the company in 1993 with a goal to create chips that accelerated graphics. Over the past thirty years, NVIDIA has gone far behind gaming and become a $674B behemoth. Jensen talks about the meaning of this broader platform shift for developers, making very long term bets in areas such as climate and biopharma, their next-gen Hopper chip, why and how NVIDIA chooses problems that are unsolvable today, and the source of his iconic leather jackets.No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode.Show Links: Jensen Huang | NVIDIA Nvidia's A100 is the $10,000 chip powering the race for A.I. | CNBC Nvidia CEO Jensen Huang: A.I. is at ‘inflection point’ | Fortune Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @NvidiaShow Notes: [1:26] - The early days when Jensen Co-founded NVIDIA[4:58] - Why NVIDIA started to expand its aperture to artificial intelligence use cases [10:42] - The moment in 2012 Jensen realized AI was going to be huge[13:52] - How we’re in a broader platform shift in computer science[17:48] - His vision for NVIDIA’s future lines of business[18:09] - How NVIDIA has two motions: Shipping reliable chips and solving new use cases [25:41] - Why no one should assume they’re right for the job of CEO and why not every company needs to be architected as the US military [31:39] - What’s next for NVIDIA’s Hopper [32:57] - Durability of Transformers [35:08] - What Jensen is excited about in the future of AI & his advice for founders

Noam Shazeer played a key role in developing key foundations of modern AI - including co-inventing Transformers at Google, as well as pioneering AI chat pre-chatGPT. These are the foundations supporting today’s AI revolution. On this episode of No Priors, Noam discusses his work as an AI researcher, engineer, inventor, and now CEO. Noam Shazeer is currently the CEO and Co-founder of Character AI, a service that allows users to design and interact with their own personal bots that take on the personalities of well-known individuals or archetypes. You could have a socratic conversation with Socrates. You could pretend you’re being interviewed by Oprah. Or you could work through a life decision with a therapist bot. Character recently raised $150M from A16Z, Elad Gil, and others. Noam talks about his early AI adventures at Google, why he started Character, and what he sees on the horizon of AI development.No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode.Show Links: Noam Shazeer - Google Scholar Noam Shazeer - Chief Executive Officer - Character.AI | LinkedIn  Character.AI Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Character_aiShow Notes: [1:50] - Noam’s early AI projects at Google[7:13] - Noam’s focus on language models and AI applications[11:13] - Character’s co-founder Daniel de Freitas Adiwardana work on Google’s Lambda[13:53] - The origin story of Character.AI [18:47] - How AI can express emotions[26:51] - What Noam looks for in new hires

If you have 30 dollars, a few hours, and one server, then you are ready to create a ChatGPT-like model that can do what’s known as instruction-following. Databricks’ latest launch, Dolly, foreshadows a potential move in the industry toward smaller and more accessible but extremely capable AIs. Plus, Dolly is open source, requires less computing power, and fewer data parameters than its counterparts.Matei Zaharia, Cofounder & Chief Technologist at Databricks, joins Sarah and Elad to talk about how big data sets actually need to be, why manual annotation is becoming less necessary to train some models, and how he went from a Berkeley PhD student with a little project called Spark to the founder of a company that is now critical data infrastructure that’s increasingly moving into AI.No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode.Show Links: Hello Dolly: Democratizing the magic of ChatGPT with open models Dolly Source Code on Github Matei Zaharia - Chief Technologist & Cofounder - Databricks | LinkedIn Matei Zaharia - Google Scholar Databricks debuts ChatGPT-like Dolly, a clone any enterprise can own | VentureBeat Sign up for new podcasts every week. Email feedback to show@no-priors.comFollow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Databricks | @Matei_ZahariaShow Notes: [01:29] - Origin of Databricks[4:30] - Work at Stanford Lab[5:29] - Dolly and Role of Open Source[12:30] - Industry focus on high parameter count, understanding reasoning at small model scale[18:42] - Enterprise applications for Dolly & chat bots[25:06] - Making bets as an academic turned CTO[36:23] - The early stages of AI and future predictions